Myocardial injury determination improves risk stratification and predicts mortality in COVID-19 patients

A study of clinical and serological correlation of early myocardial injury in elderly patients infected with the Omicron variant

Introduction

Myocardial injury in elderly Omicron variant patients is a leading cause of severe disease and death. This study focuses on elucidating the clinical characteristics and potential risk factors associated with myocardial injury in elderly patients infected with the Omicron variant.

Methods

Myocardial injury was defined based on elevated cardiac troponin concentrations exceeding the 99th percentile upper reference limit. Among 772 elderly Omicron-infected patients, categorized into myocardial injury (n = 263) and non-myocardial injury (n = 509) groups. The stratified log-rank statistic was used to compare the probability of patients developing intensive care. Receiver operating characteristic curves were used to determine the best cut-off values of clinical and laboratory data for predicting myocardial injury. Univariate and multivariate logistic regression was adopted to analyze the risk factors for myocardial injury.

Results

The occurrence of myocardial injury in Omicron variant-infected geriatric patients was up to 34.07% and these patients may have a higher rate of requiring intensive care (P < 0.05). By comparing myocardial injury patients with non-myocardial injury patients, notable differences were observed in age, pre-existing medical conditions (e.g., hypertension, coronary heart disease, cerebrovascular disease, arrhythmia, chronic kidney disease, and heart failure), and various laboratory biomarkers, including cycle threshold-ORF1ab gene (Ct-ORF1ab), cycle threshold-N gene (Ct-N), white blood cell count, neutrophil (NEUT) count, NEUT%, lymphocyte (LYM) count, LYM%, and D-dimer, interleukin-6, procalcitonin, C-reactive protein, serum amyloid A, total protein, lactate dehydrogenase, aspartate aminotransferase, glomerular filtration rate, blood urea nitrogen, and serum creatinine (sCr) levels (P < 0.05). Furthermore, in the multivariable logistic regression, we identified potential risk factors for myocardial injury in Omicron variant-infected elderly patients, including advanced age, pre-existing coronary artery disease, interleukin-6 > 22.69 pg/ml, procalcitonin > 0.0435 ng/ml, D-dimer > 0.615 mg/L, and sCr > 81.30 μmol/L.

Conclusion

This study revealed the clinical characteristics and potential risk factors associated with myocardial injury that enable early diagnosis of myocardial injury in Omicron variant-infected elderly patients, providing important reference indicators for early diagnosis and timely clinical intervention.

Predictors of lower exercise capacity in patients with cancer

Maintaining cancer patients' exercise capacity and therefore patients' ability to live a self-determined life is of huge importance, but little is known about major determinants. We sought to identify determinants of exercise capacity in patients with a broad spectrum of cancer types, who were already receiving cancer treatment or about to commence such therapy. Exercise capacity was assessed in 253 consecutive patients mostly suffering from advanced cancer using the 6-min walk test (6-MWT). All patients underwent echocardiography, physical examination, resting electrocardiogram, hand grip strength (HGS) measurement, and laboratory assessments. Patients were divided into two groups according to the median distance in the 6-MWT (459 m). Patients with lower exercise capacity were older, had significantly lower HGS and haemoglobin and higher values of high sensitive (hs) Troponin T and NT-proBNP (all p < 0.05). Whilst the co-morbidity burden was significantly higher in this group, no differences were detected for sex, body mass index, tumor type, or cachexia (all p > 0.2). Using multivariable logistic regression, we found that the presence of anaemia (odds ratio (OR) 6.172, 95% confidence interval (CI) 1.401-27.201, p = 0.016) as well as an increase in hs Troponin T (OR 3.077, 95% CI 1.202-5.301, p = 0.019) remained independent predictors of impaired exercise capacity. Increasing HGS was associated with a reduced risk of a lower exercise capacity (OR 0.896, 95% CI 0.813-0.987, p = 0.026). Screening patients for elevated hs troponin levels as well as reduced HGS may help to identify patients at risk of lower exercise capacity during cancer treatment.

Prevalence of Cardiovascular Complications in Coronavirus Disease 2019 adult Patients: A Systematic Review and Meta-Analysis

Background

It has been found that the new coronavirus can affect various parts of the cardiovascular system. Cardiovascular complications caused by coronavirus disease 2019 (COVID-19) are often serious and can increase the mortality rate among infected patients. This study aimed to investigate the prevalence of cardiovascular complications in COVID-19 adult patients.

Methods

A systematic review and meta-analysis of observational studies published in English were conducted between December 2019 and February 2021. A complete search was performed in PubMed (PubMed Central and MEDLINE), Google Scholar, Cochrane Library, Science Direct, Ovid, Embase, Scopus, CINAHL, Web of Science, and WILEY, as well as BioRXiv, MedRXiv, and gray literature. A random effect model was used to examine the prevalence of cardiovascular complications among COVID-19 patients. The I2 test was used to measure heterogeneity across the included studies.

Results

A total of 74 studies involving 34,379 COVID-19 patients were included for meta-analysis. The mean age of the participants was 61.30±14.75 years. The overall pooled prevalence of cardiovascular complications was 23.45%. The most prevalent complications were acute myocardial injury (AMI) (19.38%, 95% CI=13.62-26.81, test for heterogeneity I2=97.5%, P<0.001), arrhythmia (11.16%, 95% CI=8.23-14.96, test for heterogeneity I2=91.5%, P<0.001), heart failure (HF) (7.56%, 95% CI=4.50-12.45, test for heterogeneity I2=96.3%, P<0.001), and cardiomyopathy (2.78%, 95% CI=0.34-9.68). The highest pooled prevalence of cardiac enzymes was lactate dehydrogenase (61.45%), troponin (23.10%), and creatine kinase-myocardial band or creatine kinase (14.52%).

Conclusion

The high prevalence of serious cardiovascular complications in COVID-19 patients (AMI, arrhythmia, and HF) necessitates increased awareness by healthcare administrators.

The Potential Impact of COVID-19 Virus on the Heart and the Circulatory System

Heart attacks, arrhythmias, and cardiomyopathy are all linked to the 2019 coronavirus disease (COVID-19), which has been identified as a risk factor for cardiovascular disease. Nothing can be held accountable in the current state of affairs. Undiagnosed chronic systolic heart failure (CSHF) develops when the heart’s second half of the cardiac cycle does not function properly. As a result, the heart’s blood pumping function is interrupted. Stress-induced cardiomyopathy may be caused by a variety of factors inside the body (SICM). Cytokine storm and microvascular dysfunction are among the issues. There is inflammation in the heart muscle, which may lead to stress-induced cardiomyopathy. A major part of our study is going to be devoted to understanding the effects of coronavirus on the cardiovascular system and blood vessels. A lot of time and effort has been put into figuring out the health effects of radiation exposure. The heart and circulatory system are shown to be affected by the coronavirus in this research. COVID-19 is shown to influence persons with heart disease, heart failure, arrhythmias, microvascular angiopathy, and cardiac damage in this study.

Impact of COVID-19 on in-hospital cardiac arrest outcomes: An updated meta-analysis

BACKGROUND

The main purposes of this meta-analysis are to update the information about the impact of coronavirus disease 2019 (COVID-19) pandemic on outcomes of in-hospital cardiac arrest (IHCA) and to investigate the impact of being infected by by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) on IHCA outcomes.

METHODS

The current meta-analysis is an update and follows the recommendations of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

RESULTS

In analyses, pre- and intra-COVID-19 periods were observed for: shockable rhythms in 17.6% vs. 16.2% (odds ratio [OR]: 1.11; 95% confidence interval [CI]: 0.71-1.72; p = 0.65), return of spontaneous circulation (ROSC) in 47.4% vs. 44.0% (OR: 1.36; 95% CI: 0.90-2.07; p = 0.15), 30-day mortality in 59.8% vs. 60.9% (OR: 0.95; 95% CI: 0.75-1.22; p = 0.69) and overall mortality 75.8% vs. 74.7% (OR: 0.80; 95% CI: 0.49-1.28; p = 0.35), respectively. In analyses, SARS-CoV-2 positive and negative patients were observed for: shockable rhythms in 9.6% vs. 19.8% (OR: 0.51; 95% CI: 0.35-0.73; p < 0.001), ROSC in 33.9% vs. 52.1% (OR: 0.47; 95% CI: 0.30-0.73; p < 0.001), 30-day mortality in 77.2% vs. 59.7% (OR: 2.08; 95% CI: 1.28-3.38; p = 0.003) and overall mortality in 94.9% vs. 76.7% (OR: 3.20; 95% CI: 0.98-10.49; p = 0.05), respectively.

CONCLUSIONS

Despite ROSC, 30-day and overall mortality rate were not statistically different in pre- vs. intra-COVID-19 periods, a lower incidence of ROSC and higher 20-day mortality rate were observed in SARS-CoV-2 (+) compared to SARS-CoV-2 (-) patients.

Myocardial injuries among patients with COVID-19: a systematic review

This is a systematic review of the literature specifically aimed to explore myocardial injury in coronavirus disease-19 (COVID-19) patients who were hospitalized with severe complicated infections. The medical literature was examined through the large medical databases, including Medline, Ovid, PubMed, and Embase, over the last year between January 2020 and May 2021. The search terms used were a combination of "myocardial injury" AND "COVID-19" AND "Hospitalization". Then we applied a step to filter the results to select original research articles only evaluating the myocardial injuries in severe COVID-19 hospitalized patients. Selected trials mentioned the type of myocardial injury detected with the infection. A total of 245 articles were extracted. Considering the exclusion of ineligible articles, 42 articles appeared. A total of 42 articles were eligible and were included in the review. These studies included a total of 4326 COVID-19 patients. The 30-day mortality was found to be associated with increased cardiac troponin and myocardial infarction could be a systemic reaction rather than the direct action of COVID-19. Patients with myocardial injury were significantly older and with co-morbid conditions. Studies also found a correlation of higher concentrations of cardiac enzymes with disease severity and increased in-hospital mortality. Myocardial injury was a significant predictor for severe COVID-19 infection and in-hospital mortality. Cardiac enzymes should be monitored in hospitalized patients with severe COVID-19 infections.

Troponin I biomarker as a strong prognostic factor for predicting COVID-19 mortality: A systematic review

BACKGROUND

The increase in circulating Troponin-I in the blood of patients suffering coronavirus disease 2019 (COVID-19) can be a strong prognostic factor for predicting disease poorer outcome.

AIM

To review the literatures to approve this claim systematically.

METHODS

Two blinded reviewers independently screened the titles and abstracts of the manuscripts using the keywords and deeply searching the databanks including PubMed, Scopus, Google Scholar, and Web of knowledge, followed by profoundly appraisement of the full texts to assess the inclusion appropriateness.

RESULTS

The manuscripts entered into our final assessment were categorized as the two groups including 10 manuscripts describing and comparing death and disease-related complications between the subgroups of patients with raised serum troponin level and those with normal ranges of this biomarker and 7 manuscripts comparing the mean level of serum troponin concentration across the survived and non-survived groups. Comparing outcome of COVID-19 disease in the groups with raised troponin level and normal level of this markers showed increased the likelihood of death [hazard ratio (HR) = 4.967, P < 0.001], acute respiratory distress syndrome (HR = 5.914, P < 0.001), acute kidney injury (HR = 3.849, P < 0.001), and intensive care unit (ICU) admission (HR = 3.780, P < 0.001) following raise of troponin. The pooled analysis showed significantly higher concentration of this marker in the survived group compared to non-survived group (weighted mean differences of 22.278, 95%CI: 15.647 to 28.927, P < 0.001).

CONCLUSION

Raising troponin-I on admission can be linked to the increase risk for in-hospital death, acute respiratory distress syndrome, kidney injury, and ICU admission by 4.9, 5.9, 3.8, and 3.7 times as compared to those with initial normal troponin-I concentration. Thus, raising baseline value of troponin-I can be used as a prognostic factor for poor outcome of COVID-19.

Cardiovascular injuries and SARS-COV-2 infection: focus on elderly people

The novel coronavirus disease (COVID-19) has hit the healthcare system worldwide. The risk of severe infection and mortality increases with advancing age, especially in subjects with comorbidities such as cardiovascular disease, hypertension, diabetes, obesity and cancer. Moreover, cardiovascular complications such as myocardial injury, heart failure and thromboembolism are frequently observed in COVID-19 cases, and several biomarkers (troponin, NTproBNP and D-Dimer) have been identified as prognostic indicators of disease severity and worst outcome. Currently, there is no specific therapy against SARS-CoV-2, although many medications are under investigation. The aim of this review will be to explore the intertwined relationship between COVID-19 disease and the cardiovascular system, focusing on elderly population. The available supportive treatments along with the related concerns in elderly patients, due to their comorbidities and polypharmacotherapy, will be explored.

Predicting clinical outcomes among hospitalized COVID-19 patients using both local and published models

BACKGROUND

Many models are published which predict outcomes in hospitalized COVID-19 patients. The generalizability of many is unknown. We evaluated the performance of selected models from the literature and our own models to predict outcomes in patients at our institution.

METHODS

We searched the literature for models predicting outcomes in inpatients with COVID-19. We produced models of mortality or criticality (mortality or ICU admission) in a development cohort. We tested external models which provided sufficient information and our models using a test cohort of our most recent patients. The performance of models was compared using the area under the receiver operator curve (AUC).

RESULTS

Our literature review yielded 41 papers. Of those, 8 were found to have sufficient documentation and concordance with features available in our cohort to implement in our test cohort. All models were from Chinese patients. One model predicted criticality and seven mortality. Tested against the test cohort, internal models had an AUC of 0.84 (0.74-0.94) for mortality and 0.83 (0.76-0.90) for criticality. The best external model had an AUC of 0.89 (0.82-0.96) using three variables, another an AUC of 0.84 (0.78-0.91) using ten variables. AUC's ranged from 0.68 to 0.89. On average, models tested were unable to produce predictions in 27% of patients due to missing lab data.

CONCLUSION

Despite differences in pandemic timeline, race, and socio-cultural healthcare context some models derived in China performed well. For healthcare organizations considering implementation of an external model, concordance between the features used in the model and features available in their own patients may be important. Analysis of both local and external models should be done to help decide on what prediction method is used to provide clinical decision support to clinicians treating COVID-19 patients as well as what lab tests should be included in order sets.

How often and to what extent do admitted COVID-19 patients have signs of cardiac injury?

Background

COVID-19 can cause myocardial injury in a significant proportion of patients admitted to the hospital and seems to be associated with worse prognosis. The aim of this review was to study how often and to what extent COVID-19 causes myocardial injury and whether this is an important contributor to outcome with implications for management.

Methods

A literature search was performed in Medline and Embase. Myocardial injury was defined as elevated cardiac troponin (cTn) levels with at least one value > 99th percentile of the upper reference limit. The primary outcome measure was mortality, whereas secondary outcome measures were intensive care unit (ICU) admission and length of hospital stay.

Results

Four studies and one review were included. The presence of myocardial injury varied between 9.6 and 46.3%. Myocardial injury was associated with a higher mortality rate (risk ratio (RR) 5.54, 95% confidence interval (CI) 3.48–8.80) and more ICU admissions (RR 3.78, 95% CI 2.07–6.89). The results regarding length of hospital stay were inconclusive.

Conclusion

Patients with myocardial injury might be classified as high-risk patients, with probably a higher mortality rate and a larger need for ICU admission. cTn levels can be used in risk stratification models and can indicate which patients potentially benefit from early medication administration. We recommend measuring cTn levels in all COVID-19 patients admitted to the hospital or who deteriorate during admission.

Supplementary Information

The online version of this article (10.1007/s12471-021-01571-w) contains supplementary material, which is available to authorized users.

Impact of Coronavirus Disease 2019 on Out-of-Hospital Cardiac Arrest Survival Rate: A Systematic Review with Meta-Analysis

Out-of-hospital cardiac arrest (OHCA) is a challenge for medical staff, especially in the COVID-19 period. The COVID-19 disease caused by the SARS-CoV-2 coronavirus is highly infectious, thus requiring additional measures during cardiopulmonary resuscitation (CPR). Since CPR is a highly aerosol-generating procedure, it carries a substantial risk of viral transmission. We hypothesized that patients with diagnosed or suspected COVID-19 might have worse outcomes following OHCA outcomes compared to non-COVID-19 patients. To raise awareness of this potential problem, we performed a systematic review and meta-analysis of studies that reported OHCA in the pandemic period, comparing COVID-19 suspected or diagnosed patients vs. COVID-19 not suspected or diagnosed group. The primary outcome was survival to hospital discharge (SHD). Secondary outcomes were the return of spontaneous circulation (ROSC), survival to hospital admission or survival with favorable neurological outcomes. Data including 4210 patients included in five studies were analyzed. SHD in COVID-19 and non-COVID-19 patients were 0.5% and 2.6%, respectively (odds ratio, OR = 0.25; 95% confidence interval, CI: 0.12, 0.53; p < 0.001). Bystander CPR rate was comparable in the COVID-19 vs. not COVID-19 group (OR = 0.88; 95% CI: 0.63, 1.22; p = 0.43). Shockable rhythms were observed in 5.7% in COVID-19 patients compared with 37.4% in the non-COVID-19 group (OR = 0.19; 95% CI: 0.04, 0.96; p = 0.04; I2 = 95%). ROSC in the COVID-19 and non-COVID-19 patients were 13.3% vs. 26.5%, respectively (OR = 0.67; 95% CI: 0.55, 0.81; p < 0.001). SHD with favorable neurological outcome was observed in 0% in COVID-19 vs. 3.1% in non-COVID-19 patients (OR = 1.35; 95% CI: 0.07, 26.19; p = 0.84). Our meta-analysis suggests that suspected or diagnosed COVID-19 reduces the SHD rate after OHCA, which seems to be due to the lower rate of shockable rhythms in COVID-19 patients, but not due to reluctance to bystander CPR. Future trials are needed to confirm these preliminary results and determine the optimal procedures to increase survival after OHCA in COVID-19 patients.

A meta-analysis on the role of pre-existing chronic disease in the cardiac complications of SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been associated with multiple direct and indirect cardiovascular complications. We sought to analyze the association of host co-morbidities (chronic respiratory illnesses, cardiovascular disease [CVD], hypertension or diabetes mellitus [DM]) with the acute cardiovascular complications associated with SARS-CoV-2 infection. Individual analyses of the majority of studies found median age was higher by ~10 years in patients with cardiovascular complications. Pooled analyses showed development of SARS-CoV-2 cardiovascular complications was significantly increased in patients with chronic respiratory illness (odds ratio (OR): 1.67 [1.48, 1.88]), CVD (OR: 3.37 [2.57, 4.43]), hypertension (OR: 2.68 [2.11, 3.41]), DM (OR: 1.60 [1.31, 1.95]) and male sex (OR: 1.31 [1.21, 1.42]), findings that were mostly conserved during sub-analysis of studies stratified into global geographic regions. Age, chronic respiratory illness, CVD, hypertension, DM, and male sex may represent prognostic factors for the development of cardiovascular complications in COVID-19 disease, highlighting the need for a multidisciplinary approach to chronic disease patient management.

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Older age and male sex associated with increased SARS-CoV-2 cardiac complication risk

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Chronic illnesses associated with increased SARS-CoV-2 cardiac complication risk

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These associations were mostly conserved over differing geographical regions

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Multidisciplinary approaches to chronic disease patient management are essential

Application of a prediction model with laboratory indexes in the risk stratification of patients with COVID-19

In the present study, a prediction model with combined laboratory indexes in risk stratification of patients with COVID-19 was established and tested. The data of 170 patients with COVID-19 who were divided into an asymptomatic-moderate group (141 cases) and severe or above group (29 cases) were retrospectively analyzed. The clinical characteristics and laboratory indexes of the two groups were compared. Multivariate logistic regression analysis was performed to construct the prediction model based on laboratory indexes. A receiver operating characteristic (ROC) curve analysis was used to compare the diagnostic efficacy of different indexes. Decision curve analysis (DCA) was performed to quantify and compare the clinical validity of the prediction models. There were significant differences in blood cell count, high-sensitivity C-reactive protein (hsCRP) and procalcitonin (PCT) levels between the severe or above group and the asymptomatic-moderate group (all P<0.05). Among all individual indexes, hsCRP had the highest diagnostic efficacy (area under the curve=0.870), with a sensitivity and specificity of 0.828 and 0.802, respectively. The red blood cell count, hsCRP and PCT were used to construct the prediction model. The AUC of the prediction model was higher than that of hsCRP (0.912 vs. 0.870) but the difference was not significant (P=0.307). DCA suggested that the net benefit of the prediction model was higher than that of hsCRP in most cases and significantly higher than that of PCT, lymphocytes and monocytes. The prediction model with combined laboratory indexes was able to more effectively predict the clinical classification of patients with COVID-19 and may be used as a tool for risk stratification of patients.

Underlying heart diseases and acute COVID-19 outcomes

BACKGROUND

The presence of any underlying heart condition could influence outcomes during the coronavirus disease 2019 (COVID-19).

METHODS

The registry HOPE-COVID-19 (Health Outcome Predictive Evaluation for COVID-19, NCT04334291) is an international ambispective study, enrolling COVID-19 patients discharged from hospital, dead or alive.

RESULTS

HOPE enrolled 2798 patients from 35 centers in 7 countries. Median age was 67 years (IQR: 53.0-78.0), and most were male (59.5%). A relevant heart disease was present in 682 (24%) cases. These were older, more frequently male, with higher overall burden of cardiovascular risk factors (hypertension, dyslipidemia, diabetes mellitus, smoking habit, obesity) and other comorbidities such renal failure, lung, cerebrovascular disease and oncologic antecedents (p < 0.01, for all). The heart cohort received more corticoids (28.9% vs. 20.4%, p < 0.001), antibiotics, but less hydroxychloroquine, antivirals or tocilizumab. Considering the epidemiologic profile, a previous heart condition was independently related with shortterm mortality in the Cox multivariate analysis (1.62; 95% CI 1.29-2.03; p < 0.001). Moreover, heart patients needed more respiratory, circulatory support, and presented more in-hospital events, such heart failure, renal failure, respiratory insufficiency, sepsis, systemic infammatory response syndrome and clinically relevant bleedings (all, p < 0.001), and mortality (39.7% vs. 15.5%; p < 0.001).

CONCLUSIONS

An underlying heart disease is an adverse prognostic factor for patients suffering COVID-19. Its presence could be related with different clinical drug management and would benefit from maintaining treatment with angiotensin converting enzyme inhibitors or angiotensin receptor blockers during in-hospital stay.

Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China

OBJECTIVE

Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear.

METHODS

A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients' medical records. Multivariable logistic regression models were used to estimate the odds ratio ( OR) and 95% confidence interval (95% CI) of the associations between comorbidities (cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of COVID-19.

RESULTS

Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30-6.32), type 2 diabetes (T2DM) (3.57, 2.32-5.49), cardiovascular disease (CVD) (3.78, 1.81-7.89), fatty liver disease (7.53, 1.96-28.96), hyperlipidemia (2.15, 1.26-3.67), other lung diseases (6.00, 3.01-11.96), and electrolyte imbalance (10.40, 3.00-26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89-12.75), CVD (8.47, 6.03-11.89), and electrolyte imbalance (19.44, 11.47-32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25-9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46-29.64) within two weeks.

CONCLUSION

Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

Pre-symptomatic detection of COVID-19 from smartwatch data

Consumer wearable devices that continuously measure vital signs have been used to monitor the onset of infectious disease. Here, we show that data from consumer smartwatches can be used for the pre-symptomatic detection of coronavirus disease 2019 (COVID-19). We analysed physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, and found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which we had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, we show that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.

Prevalence and prognostic value of elevated troponins in patients hospitalised for coronavirus disease 2019: a systematic review and meta-analysis

BACKGROUND

The clinical significance of cardiac troponin measurement in patients hospitalised for coronavirus disease 2019 (covid-19) is uncertain. We investigated the prevalence of elevated troponins in these patients and its prognostic value for predicting mortality.

METHODS

Studies were identified by searching electronic databases and preprint servers. We included studies of hospitalised covid-19 patients that reported the frequency of troponin elevations above the upper reference limit and/or the association between troponins and mortality. Meta-analyses were performed using random-effects models.

RESULTS

Fifty-one studies were included. Elevated troponins were found in 20.8% (95% confidence interval [CI] 16.8-25.0 %) of patients who received troponin test on hospital admission. Elevated troponins on admission were associated with a higher risk of subsequent death (risk ratio 2.68, 95% CI 2.08-3.46) after adjusting for confounders in multivariable analysis. The pooled sensitivity of elevated admission troponins for predicting death was 0.60 (95% CI 0.54-0.65), and the specificity was 0.83 (0.77-0.88). The post-test probability of death was about 42% for patients with elevated admission troponins and was about 9% for those with non-elevated troponins on admission. There was significant heterogeneity in the analyses, and many included studies were at risk of bias due to the lack of systematic troponin measurement and inadequate follow-up.

CONCLUSION

Elevated troponins were relatively common in patients hospitalised for covid-19. Troponin measurement on admission might help in risk stratification, especially in identifying patients at high risk of death when troponin levels are elevated. High-quality prospective studies are needed to validate these findings.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020176747.

Randomized controlled study on pulmonary rehabilitation in COVID-19 patients with pneumonia

Pulmonary rehabilitation in COVID-19 patients with pneumonia is associated with better treatment outcomes. However, existing protocols have never been evaluated in randomized control studies. The aim. To evaluate the effectiveness of newly-developed pulmonary rehabilitation protocol compared to basic Russian COVID-19 guidelines for patients with oxygenation index (OI) between 200 and 400 points without IMV. Methods. Based on literature reviews and own clinical experience, standard rehabilitation protocol was designed and tailored for specific needs of low-OI patients. Two clinical centers participated in the study and included total 73 patients in main group. Control group included 73 retrospective patients based in propensity score; this patients received standard protocol of early pneumonia activation from official COVID-19 guidelines. Ten-days clinical outcomes were assessed based on parameter distribution type. Results. Evidence show significant difference in required time of continuous oxygen support in (5.1 ± 3.3 vs 8.0 ± 4.6 days for main and control group respectively. Main group also had mildly better functional. We’ve observed less mortality in main group, but attribute it not to the program, but for growing experience of health professionals and decreased loads on health system. Malignancy as comorbidity was considered a significant cofactor also. Conclusion. New pulmonary rehabilitation protocol improves clinical outcomes in critical COVID-19 patients by decreasing the demand fox oxygen support.

Early detection of elevated cardiac biomarkers to optimise risk stratification in patients with COVID-19

OBJECTIVE

Risk stratification is crucial to optimise treatment strategies in patients with COVID-19. We aimed to evaluate the impact on mortality of an early assessment of cardiac biomarkers in patients with COVID-19.

METHODS

Humanitas Clinical and Research Hospital (Rozzano-Milan, Lombardy, Italy) is a tertiary centre that has been converted to the management of COVID-19. Patients with confirmed COVID-19 were entered in a dedicated database for cohort observational analyses. Outcomes were stratified according to elevated levels (ie, above the upper level of normal) of high-sensitivity cardiac troponin I (hs-TnI), B-type natriuretic peptide (BNP) or both measured within 24 hours after hospital admission. The primary outcome was all-cause mortality.

RESULTS

A total of 397 consecutive patients with COVID-19 were included up to 1 April 2020. At the time of hospital admission, 208 patients (52.4%) had normal values for cardiac biomarkers, 90 (22.7%) had elevated both hs-TnI and BNP, 59 (14.9%) had elevated only BNP and 40 (10.1%) had elevated only hs-TnI. The rate of mortality was higher in patients with elevated hs-TnI (22.5%, OR 4.35, 95% CI 1.72 to 11.04), BNP (33.9%, OR 7.37, 95% CI 3.53 to 16.75) or both (55.6%, OR 18.75, 95% CI 9.32 to 37.71) as compared with those without elevated cardiac biomarkers (6.25%). A multivariate analysis identified concomitant elevation of both hs-TnI and BNP as a strong independent predictor of all-cause mortality (OR 3.24, 95% CI 1.06 to 9.93).

CONCLUSIONS

An early detection of elevated hs-TnI and BNP predicts mortality in patients with COVID-19. Cardiac biomarkers should be systematically assessed in patients with COVID-19 at the time of hospital admission in order to optimise risk stratification.

The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases

BACKGROUND

It is essential to study the effect of potential co-factors on the risk of death in patients infected by COVID-19. The identification of risk factors is important to allow more efficient public health and health services strategic interventions with a significant impact on deaths by COVID-19. This study aimed to identify factors associated with COVID-19 deaths in Portugal.

METHODS

A national dataset with the first 20,293 patients infected with COVID-19 between 1 January and 21 April 2020 was analyzed. The primary outcome measure was mortality by COVID-19, measured (registered and confirmed) by Medical Doctors serving as health delegates on the daily death registry. A logistic regression model using a generalized linear model was used for estimating Odds Ratio (OR) with 95% confidence intervals (95% CI) for each potential risk indicator.

RESULTS

A total of 502 infected patients died of COVID-19. The risk factors for increased odds of death by COVID-19 were: sex (male: OR = 1.47, ref = female), age ((56-60) years, OR = 6.01; (61-65) years, OR = 10.5; (66-70) years, OR = 20.4; (71-75) years, OR = 34; (76-80) years, OR = 50.9; (81-85) years, OR = 70.7; (86-90) years, OR = 83.2; (91-95) years, OR = 91.8; (96-104) years, OR = 140.2, ref = (0-55)), Cardiac disease (OR = 2.86), Kidney disorder (OR = 2.95), and Neuromuscular disorder (OR = 1.58), while condition (None (absence of precondition); OR = 0.49) was associated with a reduced chance of dying after adjusting for other variables of interest.

CONCLUSIONS

Besides age and sex, preconditions justify the risk difference in mortality by COVID-19.